Essays in Health Economics

This dissertation contains three chapters that examine how physicians make decisions and how those decisions impact patient healthcare utilization and health outcomes.The first chapter is motivated by this observation that patient referral rates vary dramatically across primary care physicians, but we know relatively little about the drivers of this variation and how this impacts patient health outcomes. In this chapter, I study how physicians with different referring styles impact patient outcomes. To separate the causal effect of physician referring style from patient related factors, I focus on a sample of Medicare patients who switch to a new primary care physician after their original primary care physician exits. I use event study analyses to compare outcomes of patients who switch to new primary care physicians with different referring styles. I find that around 35 − 38 percent of the variation in referrals across primary care physicians is due to physician referring style, with the remainder due to patient factors. Moreover, I find that high-referring physicians are associated with higher healthcare utilization and poor health outcomes. To understand the mechanisms underlying these results, I characterize high-referring physicians along various dimensions. I find that high-referring physicians work in smaller practices, see more patients, and refer their patients to a large number of providers.In the second chapter I examine the role of market mechanisms through which referring physicians learn about specialist quality. In particular, I examine how patient adverse events affect referrals from referring physicians to cardiac surgeons. I use Medicare data to identify pairs of referring physicians and cardiac specialists who have a patient adverse event within seven days of a major surgical procedure to examine how these events affect referrals. I construct counterfactuals for affected pairs using pairs that experience patient adverse event but five quarters in the future. I find that there is a significant decrease in referrals from the referring physician to the specialist after patient death. Referring physicians with below median number of referrals in the pre-event period and those that work in different practices as specialists respond more. I also examine if the physicians respond differently depending on the patient’s race, but I do not find evidence suggesting that referring physicians respond differently depending on the race of the patient who died.The third chapter examines the effect of Prescription Drug Monitoring Programs (PDMPs) on opioid use among reproductive age women and on infant health outcomes. PDMPs are state databases that track prescribing and dispensing of controlled substances. To encourage database use, several states have adopted mandatory use policy that requires prescribers to consult these databases before prescribing. I rely on the restricted-use Vital Statistics Natality files for years 2003-2018 to examine the effect of these polices on birth weight outcomes. I use Treatment Episode Data Set-Admissions (TEDS-A) for years 2003-2017 to measure opioid misuse. I estimate the effect of PDMP and mandatory use policy using a difference-in-differences framework - comparing differences in outcomes across states before and after policy adoption. PDMPs are not associated with a significant improvement in infant health outcomes. However, mandatory use of PDMPs is associated with a 0.99 percent decline in the incidence of low birth weight. PDMPs and mandatory use policy have, at best, a very small impact on population-level infant health outcomes. Moreover, there is suggestive evidence that these policies reduce prescription opioid use among reproductive age women, but leads to an increase in heroin misuse

Estimates of diagnosed dementia prevalence and incidence among diverse beneficiaries in traditional Medicare and Medicare Advantage

Abstract Approximately half of Medicare beneficiaries are enrolled in Medicare Advantage (MA), a private plan alternative to traditional Medicare (TM). Yet little is known about diagnosed dementia rates among MA enrollees, limiting population estimates. All (100%) claims of Medicare beneficiaries using encounter data for MA and claims for TM for the years 2015 to 2018 were used to quantify diagnosed dementia prevalence and incidence rates in MA, compare rates to TM, and provide estimates for the entire Medicare population and for different racial/ethnic populations. In 2017, dementia incidence and prevalence among MA beneficiaries were 2.54% (95% confidence interval [CI]: 2.53 to 2.55) and 7.04% (95% CI: 7.03 to 7.06). Comparison to TM adjusted for sociodemographic and health differences among beneficiaries in MA and TM; the prevalence of diagnosed dementia among beneficiaries in MA was lower (7.1%; 95% CI: 7.12 to 7.13) than in TM (8.7%; 95% CI: 8.71 to 8.72). The diagnosed dementia incidence rate was also lower in MA (2.50%; 95% CI: 2.50 to 2.50) compared to TM (2.99%; 95% CI: 2.99 to 2.99). There were lower rates in MA compared to TM for men and women and White, Black, Hispanic, Asian, American Indian/Alaska Native persons. Diagnosed dementia prevalence and incidence for the entire Medicare population was 7.9% (95% CI: 7.91 to 7.93) and 2.8% (95% CI: 2.77 to 2.78). Lower diagnosed dementia rates in MA compared to TM may exacerbate racial/ethnic disparities in diagnosed dementia. Rates tracked over time will provide understanding of the impact on dementia diagnosis of 2020 MA risk adjustment for dementia

Systematic failure to operate on colorectal cancer liver metastases in California.

BACKGROUND: Despite evidence that liver resection improves survival in patients with colorectal cancer liver metastases (CRCLM) and may be potentially curative, there are no population-level data examining utilization and predictors of liver resection in the United States. METHODS: This is a population-based cross-sectional study. We abstracted data on patients with synchronous CRCLM using California Cancer Registry from 2000 to 2012 and linked the records to the Office of Statewide Health Planning Inpatient Database. Quantum Geographic Information System (QGIS) was used to map liver resection rates to California counties. Patient- and hospital-level predictors were determined using mixed-effects logistic regression. RESULTS: Of the 24 828 patients diagnosed with stage-IV colorectal cancer, 16 382 (70%) had synchronous CRCLM. Overall liver resection rate for synchronous CRCLM was 10% (county resection rates ranging from 0% to 33%) with no improvement over time. There was no correlation between county incidence of synchronous CRCLM and rate of resection (R2  = .0005). On multivariable analysis, sociodemographic and treatment-initiating-facility characteristics were independently associated with receipt of liver resection after controlling for patient disease- and comorbidity-related factors. For instance, odds of liver resection decreased in patients with black race (OR 0.75 vs white) and Medicaid insurance (OR 0.62 vs private/PPO); but increased with initial treatment at NCI hospital (OR 1.69 vs Non-NCI hospital), or a high volume (10 + cases/year) (OR 1.40 vs low volume) liver surgery hospital. CONCLUSION: In this population-based study, only 10% of patients with liver metastases underwent liver resection. Furthermore, the study identifies wide variations and significant population-level disparities in the utilization of liver resection for CRCLM in California